clarify classification docs

prevents duplicate key warnings when users mix vaapi and qsv

docs/docs/configuration/object_detectors.md

@@ -175,7 +175,7 @@ model:
   width: 320 # <--- should match the imgsize of the model, typically 320
   height: 320 # <--- should match the imgsize of the model, typically 320
   path: /config/model_cache/yolov9-s-relu6-best_320_int8_edgetpu.tflite
-  labelmap_path: /config/labels-coco17.txt
+  labelmap_path: /labelmap/labels-coco-17.txt
 ```
 
 Note that the labelmap uses a subset of the complete COCO label set that has only 17 objects.

docs/static/frigate-api.yaml

@@ -17,25 +17,20 @@ paths:
       summary: Authenticate request
       description: |-
         Authenticates the current request based on proxy headers or JWT token.
+        Returns user role and permissions for camera access.
         This endpoint verifies authentication credentials and manages JWT token refresh.
-        On success, no JSON body is returned; authentication state is communicated via response headers and cookies.
       operationId: auth_auth_get
       responses:
+        "200":
+          description: Successful Response
+          content:
+            application/json:
+              schema: {}
         "202":
-          description: Authentication Accepted (no response body, different headers depending on auth method)
+          description: Authentication Accepted
-          headers:
+          content:
-            remote-user:
+            application/json:
-              description: Authenticated username or "anonymous" in proxy-only mode
+              schema: {}
-              schema:
-                type: string
-            remote-role:
-              description: Resolved role (e.g., admin, viewer, or custom)
-              schema:
-                type: string
-            Set-Cookie:
-              description: May include refreshed JWT cookie ("frigate-token") when applicable
-              schema:
-                type: string
         "401":
           description: Authentication Failed
   /profile:

frigate/detectors/detection_runners.py

@@ -131,7 +131,6 @@ class ONNXModelRunner(BaseModelRunner):
 
         return model_type in [
             EnrichmentModelTypeEnum.paddleocr.value,
-            EnrichmentModelTypeEnum.yolov9_license_plate.value,
             EnrichmentModelTypeEnum.jina_v1.value,
             EnrichmentModelTypeEnum.jina_v2.value,
             EnrichmentModelTypeEnum.facenet.value,

frigate/ffmpeg_presets.py

@@ -153,7 +153,7 @@ PRESETS_HW_ACCEL_ENCODE_BIRDSEYE = {
     FFMPEG_HWACCEL_VAAPI: "{0} -hide_banner -hwaccel vaapi -hwaccel_output_format vaapi -hwaccel_device {3} {1} -c:v h264_vaapi -g 50 -bf 0 -profile:v high -level:v 4.1 -sei:v 0 -an -vf format=vaapi|nv12,hwupload {2}",
     "preset-intel-qsv-h264": "{0} -hide_banner {1} -c:v h264_qsv -g 50 -bf 0 -profile:v high -level:v 4.1 -async_depth:v 1 {2}",
     "preset-intel-qsv-h265": "{0} -hide_banner {1} -c:v h264_qsv -g 50 -bf 0 -profile:v main -level:v 4.1 -async_depth:v 1 {2}",
-    FFMPEG_HWACCEL_NVIDIA: "{0} -hide_banner {1} -hwaccel cuda -hwaccel_device {3} -c:v h264_nvenc -g 50 -profile:v high -level:v auto -preset:v p2 -tune:v ll {2}",
+    FFMPEG_HWACCEL_NVIDIA: "{0} -hide_banner {1} -hwaccel device {3} -c:v h264_nvenc -g 50 -profile:v high -level:v auto -preset:v p2 -tune:v ll {2}",
     "preset-jetson-h264": "{0} -hide_banner {1} -c:v h264_nvmpi -profile high {2}",
     "preset-jetson-h265": "{0} -hide_banner {1} -c:v h264_nvmpi -profile main {2}",
     FFMPEG_HWACCEL_RKMPP: "{0} -hide_banner {1} -c:v h264_rkmpp -profile:v high {2}",